Lecture 9-16 - Individual Cognition.docx

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School

University of British Columbia

Department

Psychology

Course

PSYC 309

Professor

Todd Handy

Semester

Fall

Description

Lecture NYT Research Paper
Blind to Change
Cost attention-grabbing - Bottom-Up Attention - The reflexive or
urban stimulation automatic tendency of our visual attention to get
Attention drawn to “eye-catching” stimuli, such as a
­ Cognitive effort try to shut flashing light or uniquely-coloured object; “the Forster (2012)
- We are typically unaware of our global/local state, or
out distracting stimulation; optical equivalent of a shout” what they refer to as “processing style” (Part 2)
­ Berman (2008) subconscious override to
inhibit bottom-up attention - Top-Down Attention – The conscious, willful
– Bottom-up decision to attend to some specific aspect or - Can “prime” broader (global) vs. narrower (local)
Attention: effect detail of the visual environment semantic categories; this is the link between
9 nature/urban “perceptual scope” and “conceptual scope” (L. 10)
­ Looking at same picture –
depending on what we know ­ Change blindness: frequent inability of our - Exposure to novel events triggers a global
-> see different things visual system to detect alterations to something
in plain view processing style, but if they are “threatening”, then it
­ Werner & Ties ­ Knowledge can help guide ­ Visual system can focus on only one or very triggers a local processing style (L. 11)
– Top-down few objects at a time; lot of detail we don’t pick
Attention: football where we put our attention, up on
impact what we do with top- ­ Brain – master at filling gaps; compiling
down attention cohesive portrait of reality
­ Depending on knowledge, change in detail
may or may not make a difference
10 Priming Blue Room, Red Room – Zhu (2009) Mehta (2009)
How do you explain the idea of ­ Associations – activated without a person’s o “Approach” anagrams solved more quickly
conceptual effect of global/local in awareness  influence what they are thinking on computer with a blue desktop. ”avoidance”
respect to semantic association? about or doing
- Bargh (1996): anagrams solved more quickly on computer w/
red background.
- Priming age • Local frame of mind – ­ Colors may affect cognitive performance
activating fewer network because of the moods they engender • When asked to memorize a list of words,
stereotypes participants recalled significantly more words
• Global state of mind – ­ Brightness or intensity of colour, not just
- Priming colour itself, might have had an effect when the list was shown on a computer with a
rudeness broader network red background, relative to a blue or neutral
­ Effects occur outside of individuals’ background.
- • Red and blue activate
different motivations, enhance performances • When asked to generate as many uses for a
on different types of brick as they could think of, participants who
cognitive tasks worked on a computer with a blue background
produced significantly more creative uses,
• Color theorists: color consciousness relative to those who did the task with a red or
influences cognition and
­ Red: danger, mistakes, hazard, highest neutral background.
behaviour through level of compliance  avoidance motivation
learned associations • Proof-reading to assess attention to “detail”;
remote associations test to assess creativity.
• Conclusion: red vs. blue ­ Make people more vigilant, risk adverse 
detailed oriented, focus, careful
can activate avoidance • Design a toy from a choice of parts, then have the
motivation, enhance ­ Blue: openness, peace, tranquility  design rated for originality (creativity) and practicality
performance on detailed approach motivation (attention to detail).
oriented cognitive tasks
­ Benign environment, innovative  explorative, • Evaluate the persuasiveness of an ad that
risky manner included product details vs. potential uses of the
object
­
• Rate preference for a brand that emphasizes
“prevention” vs. “approach” focus of the product
­
Implicit Learning Nonesense Bulf (2011)
11 • “Sensation of the absurd” - an experience • Statistical learning – implicit learning of
that violates all logic and expectation statistical regularities within sensory input
­ HM – amnesia • Study: same sensation may prime the brain o Way of acquiring structure within continuous
sensory environments
­ Classical to sense patterns it would otherwise miss
conditioning
o Get rid of that feeling, look for meaning, • Trying to make visual analogy using shapes
­ coherence
• Newborns habituated to one of two stimulus
• Dr Proulx and Steven J Heine: maintaining
patterns: A more complex one (left, HDC – High
meaning or coherence demand condition) or a simpler one (right, LDC – • Study 1 – reading task Low demand condition)
o Group who read absurd story – identified • possibility that statistical learning is
more letter strings = more motivated to look influenced by the restricted cognitive capacities
for patterns than others; forming new of newborn infants, or whether its functioning
patterns they wouldn’t be able to form does not differ from statistical learning shown
otherwise by older infants
o Spur heightened sensitivity to statistical • high demand condition (HDC) – 3 sets of
probability, learning associations shapes
o Amount of looking time, kids didn’t show
• Study 2 – make an argument about
themselves preference between old/new pattern
• Non-sense (condition 1) – exposed to this o Not picking up on probabilities, more information
than they can be sensitive to
situation, increased sensitivity pattern in
world, trigger statistical domain learning
mechanism • low demand condition (LDC) – 2 sets of shapes
• Artificial Grammar Task o spent more time looking at random sequence
than the one they were habituated to
• 45 letter strings with certain predictable
transition properties (mimic common letter o Preferential looking evidence - they did learn the
simple sequence, liked looking at random one better
combinations in regular language)
• Result: newborn learner’s limited cognitive
• “surprise” memory test – 60 letter strings,
which strings they have seen, which new resources constrain the functioning of statistical
learning, narrowing the range of what can be
(30, 30) learned
• Issue: whether memory performance was
affected by which story they read •
• Memory performance better, significantly
more letter strings recognized by group that got
nonsense (Kafka, Argue something they are not)
• To pick up on transition probability – need to
pay attention to details
o Triggers heightened attentional state, pick up
on letter strings – local state, priming, details,
alert
• The “Meaning Maintenance” Hypothesis
o Exposure to situations where your sense
of patterns breaks down (i.e., when things
don’t make sense) can spur your statistical
learning system into action, as a means of
helping to maintain a continuous state
(achieve new level) of understanding.
12 Unconscious Unconscious Mind Dijksterhuis (2006)
Thinking • People struggling to make complex • ‘‘deliberation-without-attention’’ hypothesis -
decisions did best when they were purchases of complex products were viewed more
distracted, and were not able to think favorably when decisions had been made in the
­ Schooler consciously about the choice at all absence of attentive deliberation.
(1993)
• relation between mode of thought/deliberation
(conscious vs. unconscious) and complexity
­ Reasoning • Study 1
problem (capacity of information) and quality of choice
o 4 cars; 4 attributes (simple) or 12 attributes (satisfaction)
­ Insight
problem (complex) ­ Conscious thought – deliberation/thought while
conscious attention is directed at problem at hand
o Conscious – think for 4 mins
­ rule-based, very precise; necessary to follow
 Proper choice under simple, poorly under complex strict rules
o Unconscious – distracted for 4 mins, then o Conscious thought suffers from low capacity
choose of consciousness, less suitable for very complex
issues
• Study 2
• Unconscious thought – thought/deliberation in
o Attitudes toward each of 4 cars
absence of conscious attention directed at the
o Conscious – able to differentiate quality of problem
cars under simple o sudden thought pops into consciousness;
indecision  preference, results of unconscious
o Unconscious – better able to differentiate
quality of cars under complex thought
o conform to rules in that it detects recurring
• Study 3 patterns, as implicit learning shows
o Aspects of a product taken into account in 40
different products = “complexity score” o does not suffer from lower capacity; large
amounts of information can be integrated into an
evaluative summary judgment
o Actual study, students presented with list of
40 products
• Why conscious deliberation sometimes leads to
o Thinking does not make people more poor judgments
satisfied, nor does complexity o Consciousness has a low capacity – choosers
o Correlation calculated between thought and take into account only a subset of relevant
post-choice satisfaction information
o Lead to suboptimal weighting of importance of
 Medium complexity – no correlation attributes; inflate importance of some attributes at
 Simple – positive correlation the expense of others  worse choices; equal
weighting to unequal factors (e.g. making a list)
• More people thought consciously about
• Conscious thinkers were better able to make
simple, more satisfied
the best choice among simple products,  Complex – negative correlation
• More conscious thought about complex, less
satisfied
whereas unconscious thinkers were better able